Showing 1–20 of 37 results
/ Date/ Name
Oct 19, 2020A Framework to Learn with InterpretationApr 14, 2026Finetuning-Free Diffusion Model with Adaptive Constraint Guidance for Inorganic Crystal Structure GenerationDec 26, 2023Abnormal component analysisFeb 9, 2021Emotion Transfer Using Vector-Valued Infinite Task LearningJul 29, 2020Learning Output Embeddings in Structured PredictionDec 21, 2023Fast kernel half-space depth for data with non-convex supportsApr 9, 2019Functional Isolation ForestMar 13, 2020Flexible and Context-Specific AI Explainability: A Multidisciplinary ApproachJun 18, 2020When OT meets MoM: Robust estimation of Wasserstein DistanceFeb 19, 2024Any2Graph: Deep End-To-End Supervised Graph Prediction With An Optimal Transport LossOct 10, 2019Duality in RKHSs with Infinite Dimensional Outputs: Application to Robust LossesMay 28, 2025The quest for the GRAph Level autoEncoder (GRALE)May 22, 2018Infinite-Task Learning with RKHSsMar 27, 2020Improving Reproducibility in Machine Learning Research (A Report from the NeurIPS 2019 Reproducibility Program)Jun 8, 2022Fast Kernel Methods for Generic Lipschitz Losses via $p$-Sparsified SketchesAug 29, 2019From the Token to the Review: A Hierarchical Multimodal approach to Opinion MiningApr 20, 2022Wind power predictions from nowcasts to 4-hour forecasts: a learning approach with variable selectionFeb 26, 2019A multimodal movie review corpus for fine-grained opinion miningFeb 8, 2022Learning to Predict Graphs with Fused Gromov-Wasserstein BarycentersFeb 23, 2022Listen to Interpret: Post-hoc Interpretability for Audio Networks with NMF